This guide gives {{Company name}} a structured loop for software engineering roles, from backend and frontend engineers to fullstack and infrastructure hires. The loop tests what the job actually requires — writing working code, designing systems under constraints, reviewing other people's code, and operating what they ship — instead of puzzle trivia. Every stage has an assigned interviewer, a question bank, and shared scoring anchors.

Stage plan

Competency map

• Coding fluency — writes correct, readable code, tests it, and debugs methodically when it breaks.
• System design — decomposes problems, names trade-offs explicitly, and scales the design only as far as the requirements demand.
• Code quality and review — gives precise, kind, prioritized feedback and distinguishes blocking issues from preferences.
• Operational maturity — thinks about monitoring, failure modes, rollout, and on-call before being asked.
• Collaboration and communication — explains reasoning clearly, asks for missing context, and disagrees productively.

Question banks by stage

Hiring manager interview

• Walk me through the system you know best. What would you rebuild differently?
• Tell me about the worst incident you were involved in. What was your role and what changed afterwards?
• What is the largest piece of work you scoped and delivered end to end?
• Tell me about a technical decision you got wrong. How did you find out?
• How do you decide between fixing tech debt and shipping features?
• What does code ownership mean on your current team, and what would you change?

Coding interview

Use a realistic task in the candidate's chosen language — extending a small service, fixing a failing test suite, or implementing a well-scoped feature. Allow documentation and normal tooling.

• Implement the feature: do they clarify requirements and edge cases before coding?
• Introduce a failing test or a planted bug: how do they narrow it down?
• Ask them to add tests: do they cover the boundaries or just the happy path?
• Ask for a refactor of one gnarly function: does readability actually improve?
• Ask how they would ship this change safely to production.
• Ask what they would do differently with another day of time.

System design interview

Pick a problem adjacent to your product — a notifications pipeline, a rate limiter, a file-processing service. State scale explicitly and change it mid-interview.

• What questions do they ask before drawing anything?
• Have them sketch the core data model and API surface: is it minimal and coherent?
• Double the traffic and add a latency budget: what breaks first and what changes?
• Where does this design lose data, and how would they know?
• What would they build first, and what would they defer?
• How would they migrate from the current system with zero downtime?

Code review and collaboration

Prepare a pull request with a mix of real problems: a subtle bug, a missing test, an unclear name, and one over-engineered abstraction.

• Which issues do they flag as blocking versus nitpicks?
• Do they catch the subtle bug, and how do they verify it?
• How do they phrase feedback — specific and kind, or vague and harsh?
• Ask them to defend a change the author might push back on.
• What would they praise in this PR? Reviewers who only find faults miss half the job.

Scoring anchors

Score each competency 1 to 4 with written evidence immediately after each stage. Calibrate the bar to the level being hired: at senior levels weight system design and operational maturity most heavily.

• 1 — Below bar: code does not run and debugging is guesswork; designs skip requirements; feedback is vague or unkind.
• 2 — Near bar: reaches working solutions with significant hints; names trade-offs only when prompted.
• 3 — At bar: works methodically, tests without being asked, states trade-offs and failure modes unprompted.
• 4 — Above bar: simplifies the problem before solving it, anticipates operational concerns, and communicates so clearly the interviewer learns something.